Sjoerd Kelder is a data scientist specializing in scaling machine learning workflows on high-performance computing systems. For his MSc in Information Studies (UvA, 2025) he used SURF’s Snellius HPC system to benchmark deep learning models with extended feature sets on large datasets. He now works with Fearless League on AI-powered lab tooling and reproducible ML infrastructure. His interests include workflow design, reproducibility practices, and efficient deployment of ML pipelines on large compute resources, applicable across sectors from science to industry.

University of Amsterdam (MSc Information Studies, 2025) / Fearless League (AI R&D)